LUXEMBOURG—Regenerative medicine and the potential of stem cells continue to occupy researchers in the search for new options in disease treatment, wound healing and other indications. One of the latest discoveries in this search comes from a team of scientists from the Computational Biology group of the Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg. Together with researchers from the Karolinska Institutet in Sweden, the team demonstrated a method by which they could accurately predict how to reprogram one subpopulation of cells into another.

This research, detailed in a paper titled “Transcriptional synergy as an emergent property defining cell subpopulation identity enables population shift,” appeared in Nature Communications.

“The method has great potential for regenerative medicine when it comes to replacing cell subpopulations that have been lost in the course of disease, for example,” said Dr. Antonio del Sol, head of the Computational Biology group at the LCSB.

Their work, as noted by the authors in the abstract of the paper, is based on the hypothesis that “subpopulation identity emerges from the synergistic activity of multiple TFs [transcription factors]. Based on this concept, we develop a computational platform (TransSyn) for identifying synergistic transcriptional cores that determine cell subpopulation identities. TransSyn leverages single-cell RNA-seq data and performs a dynamic search for an optimal synergistic transcriptional core using an information theoretic measure of synergy. A large-scale TransSyn analysis identifies transcriptional cores for 186 subpopulations and predicts identity conversion TFs between 3786 pairs of cell subpopulations. Finally, TransSyn predictions enable experimental conversion of human hindbrain neuroepithelial cells into medial floor plate midbrain progenitors, capable of rapidly differentiating into dopaminergic neurons.”

The authors explain that while there are existing methods to identify transcription factors responsible for cellular identity or conversion, they “rely on a set of gene expression profiles of bulk cell/tissue types,” and as such are limited to those types. “In addition, these methods detect potential identity TFs by focusing on properties of individual TFs, such as gene expression levels or the number of their unique target genes, rather than emergent properties of potential identity TFs themselves,

such as transcriptional synergy among them,” they write.

“The identity of a particular cell subtype is characterized and maintained by a few interacting regulatory genes,” del Sol noted in a press release. “Yet the differences between the subtypes are subtle and difficult to detect using the existing analytical methods.”

TransSyn looks at the gene expression profiles of individual cells within a given population, and using a multistep computational pipeline, it locates differences between cell subtypes. As noted in a University of Luxembourg press release, there are “multiple synergistically interacting regulatory genes working together to characterize a subtype,” or “transcriptional cores.”

“It is based on the assumption that cell identity is determined by a few transcription factors (TFs) that are synergistically interacting with each other,” explains Satoshi Okawa, first author of the paper. “It measures this synergy by an information theoretic metric called multivariate mutual information. As computing this metric for all combinations of TFs is computationally impractical, it identifies highly synergistic TFs by a heuristic algorithm.”

Once these cores are identified, the researchers have enough information to attempt to convert cell subtypes in the lab through the application of the necessary transcription factors. The collaborators tested this at the Karolinska Institutet by converting human neuroepithelial stem cells into dopaminergic neuron progenitors that could develop into dopaminergic neurons. Seeing as how a subtype of dopaminergic neurons in the substantia nigra section of the midbrain are slowly lost in Parkinson’s disease, a method for regenerating that specific subpopulation could have important implications in treating the neurodegenerative disease.

Work is underway to test the TransSyn approach further, as the University of Luxembourg team is now collaborating with the Gladstone Institute in the United States to see if this could provide a more streamlined way to convert heart cells from the right ventricle into heart cells of the left ventricle, and vice-versa.

Satoshi Okawa, first author of the paper, says that with regards to other cell types they hope to explore with TransSyn, “As our method is intended to be generally applicable to any kind of cells, we do not have a special interest in a certain cell type. However, we particularly aim to deal with subtypes of cell types that are often not easy to tell apart. Those subtypes, however, can exhibit important functional differences, and therefore are of clinical interest.” He notes that they also hope to explore “how synergistic identity TFs found by TransSyn are connected to each other to collectively maintain cell identity. We are trying to computationally tackle this problem by, for example, building gene regulatory networks around those TFs.”